Here, we’re just setting a few options.

knitr::opts_chunk$set(
  warning = FALSE, # show warnings during codebook generation
  message = FALSE, # show messages during codebook generation
  error = TRUE, # do not interrupt codebook generation in case of errors,
                # usually better for debugging
  echo = TRUE  # show R code
)
ggplot2::theme_set(ggplot2::theme_bw())

Now, we’re preparing our data for the codebook.

library(codebook)
library(formr)
# library(labelled)
# library(ufs)
# library(GGally)

############################################################################## #
###   THESE ARE THE ONLY TWO LINES OF CODE THAT I NEED TO ENTER     ########## #
############################################################################## #

# formr_store_keys("juergen") # save my login credentials (do just once)
formr_connect(keyring = "juergen") # retreive credentials and login to formr

codebook_data <- formr_results("codebook_workshop") # pulls survey results
                                                    # also aggregates items with 
                                                    # the same name and continuous
                                                    # numbers at the end




# to import an SPSS file from the same folder uncomment and edit the line below
# codebook_data <- rio::import("mydata.sav")
# for Stata
# codebook_data <- rio::import("mydata.dta")
# for CSV
# codebook_data <- rio::import("mydata.csv")

# omit the following lines, if your missing values are already properly labelled
codebook_data <- detect_missing(codebook_data,
    only_labelled = TRUE, # only labelled values are autodetected as
                                   # missing
    negative_values_are_missing = FALSE, # negative values are missing values
    ninety_nine_problems = TRUE,   # 99/999 are missing values, if they
                                   # are more than 5 MAD from the median
    )

# If you are not using formr, the codebook package needs to guess which items
# form a scale. The following line finds item aggregates with names like this:
# scale = scale_1 + scale_2R + scale_3R
# identifying these aggregates allows the codebook function to
# automatically compute reliabilities.
# However, it will not reverse items automatically.

codebook_data <- detect_scales(codebook_data)

Create codebook

codebook(codebook_data)

Metadata

Description

Dataset name: codebook_data

The dataset has N=41 rows and 14 columns. 0 rows have no missing values on any column.

Metadata for search engines
  • Date published: 2023-02-13
x
session
created
modified
ended
expired
sof_1
sof_2
sof_3
cbk
rmd_01
rmd_02
rmd_03
sof
rmd

Survey overview

39 completed rows, 39 who entered any information, 2 only viewed the first page. There are 0 expired rows (people who did not finish filling out in the requested time frame). In total, there are 41 rows including unfinished and expired rows.

There were 41 unique participants, of which 39 finished filling out at least one survey.

This survey was not repeated.

The first session started on 2023-02-13 10:36:26, the last session on 2023-02-13 10:59:53.

Starting date times

Starting date times

People took on average 0.76 minutes (median 0.67) to answer the survey.

Duration people took for answering the survey

Duration people took for answering the survey

Variables

cbk

Hatten Sie schon die Gelegenheit das codebook package auszuprobieren?

Distribution

Distribution of values for cbk

Distribution of values for cbk

2 missing values.

Summary statistics

name label type data_type optional showif value item_order block_order class n_missing complete_rate min median max mean sd n_value_labels hist
cbk Hatten Sie schon die Gelegenheit das codebook package auszuprobieren? mc_button haven_labelled 0 5 2 0.9512195 1 1 2 1.128205 0.3386884 4 ▇▁▁▁▁▁▁▁

Item

Item options
type name label optional class showif value block_order item_order
mc_button cbk Hatten Sie schon die Gelegenheit das codebook package auszuprobieren? 0 5

Value labels

Response choices
name value
nein 1
kurz reingeschaut 2
ja 3
Item was never rendered for this user. NA

Scale: sof

Overview

Reliability: ωtotal [95% CI] = 0.82 [not computed].

Missing: 2.

Likert plot of scale sof items

Likert plot of scale sof items

Distribution of scale sof

Distribution of scale sof

Reliability details

Scale diagnosis
Reliability (internal consistency) estimates
Scale structure
Information about this scale
Dataframe: res$dat
Items: sof_1, sof_2 & sof_3
Observations: 39
Positive correlations: 3
Number of correlations: 3
Percentage positive correlations: 100
Estimates assuming interval level
Omega (total): 0.82
Omega (hierarchical): 0.41
Revelle’s Omega (total): 0.87
Greatest Lower Bound (GLB): 0.90
Coefficient H: 1.00
Coefficient Alpha: 0.78
Estimates assuming ordinal level
Ordinal Omega (total): NA
Ordinal Omega (hierarch.): NA
Ordinal Coefficient Alpha: 0.91

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

2.202, 0.79 & 0.008

Factor analysis (reproducing only shared variance)
ML1
sof_1 0.995
sof_2 0.998
sof_3 0.359
Component analysis (reproducing full covariance matrix)
PC1
sof_1 0.966
sof_2 0.970
sof_3 0.572
Item descriptives
mean median var sd IQR se min q1 q3 max skew kurt dip n NA valid
sof_1 5.5385 6 1.6235 1.2742 0 0.204 1 3 NA 6 -2.9064 7.6605 0.0256 39 0 39
sof_2 5.5128 6 1.6248 1.2747 0 0.2041 1 3 NA 6 -2.8426 7.3858 0.0385 39 0 39
sof_3 5.1538 6 2.3441 1.5311 1 0.2452 1 3.5 NA 6 -1.8028 2.2269 0.0385 39 0 39
Scattermatrix
Scatterplot

Scatterplot

Summary statistics

name label type type_options data_type value_labels optional showif value item_order block_order class n_missing complete_rate min median max mean sd n_value_labels hist
sof_1 Haben Sie eine aktuelle R-Version installiert? rating_button 1,6,1 haven_labelled 1. 1: hat nicht geklappt,
2. 2,
3. 3,
4. 4,
5. 5,
6. 6: hat problemlos geklappt,
NA. Item was never rendered for this user.		 0 2 2 0.9512195 1 6 6 5.538462 1.274159 7 ▁▁▁▁▁▁▁▇
sof_2 Haben Sie eine aktuelle RStudio-Version installiert? rating_button 1,6,1 haven_labelled 1. 1: hat nicht geklappt,
2. 2,
3. 3,
4. 4,
5. 5,
6. 6: hat problemlos geklappt,
NA. Item was never rendered for this user.		 0 3 2 0.9512195 1 6 6 5.512821 1.274689 7 ▁▁▁▁▁▁▁▇
sof_3 Haben Sie das codebook package installiert? rating_button 1,6,1 haven_labelled 1. 1: hat nicht geklappt,
2. 2,
3. 3,
4. 4,
5. 5,
6. 6: hat problemlos geklappt,
NA. Item was never rendered for this user.		 0 4 2 0.9512195 1 6 6 5.153846 1.531055 7 ▁▁▁▁▁▁▁▇

Scale: rmd

Overview

Reliability: ωordinal [95% CI] = 0.87 [0.79;0.94].

Missing: 2.

Likert plot of scale rmd items

Likert plot of scale rmd items

Distribution of scale rmd

Distribution of scale rmd

Reliability details

Scale diagnosis
Reliability (internal consistency) estimates
Scale structure
Information about this scale
Dataframe: res$dat
Items: rmd_01, rmd_02 & rmd_03
Observations: 39
Positive correlations: 3
Number of correlations: 3
Percentage positive correlations: 100
Estimates assuming interval level
Omega (total): 0.84
Omega (hierarchical): 0.02
Revelle’s Omega (total): 0.84
Greatest Lower Bound (GLB): 0.84
Coefficient H: 0.84
Coefficient Alpha: 0.84

Confidence intervals

Omega (total): [0.76; 0.93]
Coefficient Alpha: [0.75; 0.93]
Estimates assuming ordinal level
Ordinal Omega (total): 0.87
Ordinal Omega (hierarch.): 0.84
Ordinal Coefficient Alpha: 0.87

Confidence intervals

Ordinal Omega (total): [0.79; 0.94]
Ordinal Coefficient Alpha: [0.79; 0.94]

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

2.28, 0.378 & 0.342

Factor analysis (reproducing only shared variance)
ML1
rmd_01 0.782
rmd_02 0.798
rmd_03 0.820
Component analysis (reproducing full covariance matrix)
PC1
rmd_01 0.865
rmd_02 0.871
rmd_03 0.879
Item descriptives
mean median var sd IQR se min q1 q3 max skew kurt dip n NA valid
rmd_01 3.2564 4 2.5641 1.6013 2 0.2564 1 2 5 6 -0.0379 -1.1374 0.1026 39 0 39
rmd_02 3.4103 4 2.4062 1.5512 3 0.2484 1 2 5 6 0.0206 -1.0165 0.1026 39 0 39
rmd_03 4.1282 4 3.3779 1.8379 3 0.2943 1 2 6 6 -0.5203 -1.0912 0.0812 39 0 39
Scattermatrix
Scatterplot

Scatterplot

Summary statistics

name label type type_options data_type value_labels optional showif value item_order block_order class n_missing complete_rate min median max mean sd n_value_labels hist
rmd_01 Wie oft haben Sie schon mit R Markdown gearbeitet? rating_button 1,6,1 haven_labelled 1. 1: noch nie,
2. 2,
3. 3,
4. 4,
5. 5,
6. 6: sehr oft,
NA. Item was never rendered for this user.		 0 6 2 0.9512195 1 4 6 3.256410 1.601282 7 ▆▅▁▃▇▁▅▂
rmd_02 Ich weiß, wie ich in R Markdown Textformatierungen vornehmen kann. rating_button 1,6,1 haven_labelled 1. 1: gar nicht,
2. 2,
3. 3,
4. 4,
5. 5,
6. 6: vollständig,
NA. Item was never rendered for this user.		 0 7 2 0.9512195 1 4 6 3.410256 1.551196 7 ▃▆▁▅▇▁▅▃
rmd_03 Ich weiß, wie ich in R Markdown ein HTML Dokument erstelle, in dem der Analysecode und die Ergebnisse meiner statistischen Auswertungen enthalten sind. rating_button 1,6,1 haven_labelled 1. 1: hell no,
2. 2,
3. 3,
4. 4,
5. 5,
6. 6: hell yes,
NA. Item was never rendered for this user.		 0 8 2 0.9512195 1 4 6 4.128205 1.837898 7 ▃▁▁▃▃▁▃▇

Missingness report

Codebook table

JSON-LD metadata

The following JSON-LD can be found by search engines, if you share this codebook publicly on the web.

{
  "name": "codebook_data",
  "datePublished": "2023-02-13",
  "description": "The dataset has N=41 rows and 14 columns.\n0 rows have no missing values on any column.\n\n\n## Table of variables\nThis table contains variable names, labels, and number of missing values.\nSee the complete codebook for more.\n\n|name     |label                                                                                                                                                   | n_missing|\n|:--------|:-------------------------------------------------------------------------------------------------------------------------------------------------------|---------:|\n|session  |NA                                                                                                                                                      |         0|\n|created  |user first opened survey                                                                                                                                |         0|\n|modified |user last edited survey                                                                                                                                 |         2|\n|ended    |user finished survey                                                                                                                                    |         2|\n|expired  |NA                                                                                                                                                      |        41|\n|sof_1    |Haben Sie eine aktuelle R-Version installiert?                                                                                                          |         2|\n|sof_2    |Haben Sie eine aktuelle RStudio-Version installiert?                                                                                                    |         2|\n|sof_3    |Haben Sie das codebook package installiert?                                                                                                             |         2|\n|cbk      |Hatten Sie schon die Gelegenheit das codebook package auszuprobieren?                                                                                   |         2|\n|rmd_01   |Wie oft haben Sie schon mit R Markdown gearbeitet?                                                                                                      |         2|\n|rmd_02   |Ich weiß, wie ich in R Markdown Textformatierungen vornehmen kann.                                                                                      |         2|\n|rmd_03   |Ich weiß, wie ich in R Markdown ein HTML Dokument erstelle, in dem der Analysecode und die Ergebnisse meiner statistischen Auswertungen enthalten sind. |         2|\n|sof      |aggregate of 3 sof items                                                                                                                                |         2|\n|rmd      |aggregate of 3 rmd items                                                                                                                                |         2|\n\n### Note\nThis dataset was automatically described using the [codebook R package](https://rubenarslan.github.io/codebook/) (version 0.9.4.9000).",
  "keywords": ["session", "created", "modified", "ended", "expired", "sof_1", "sof_2", "sof_3", "cbk", "rmd_01", "rmd_02", "rmd_03", "sof", "rmd"],
  "@context": "http://schema.org/",
  "@type": "Dataset",
  "variableMeasured": [
    {
      "name": "session",
      "@type": "propertyValue"
    },
    {
      "name": "created",
      "description": "user first opened survey",
      "@type": "propertyValue"
    },
    {
      "name": "modified",
      "description": "user last edited survey",
      "@type": "propertyValue"
    },
    {
      "name": "ended",
      "description": "user finished survey",
      "@type": "propertyValue"
    },
    {
      "name": "expired",
      "@type": "propertyValue"
    },
    {
      "name": "sof_1",
      "description": "Haben Sie eine aktuelle R-Version installiert?",
      "value": "1. 1: hat nicht geklappt,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6: hat problemlos geklappt,\nNA. Item was never rendered for this user.",
      "maxValue": 6,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sof_2",
      "description": "Haben Sie eine aktuelle RStudio-Version installiert?",
      "value": "1. 1: hat nicht geklappt,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6: hat problemlos geklappt,\nNA. Item was never rendered for this user.",
      "maxValue": 6,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sof_3",
      "description": "Haben Sie das codebook package installiert?",
      "value": "1. 1: hat nicht geklappt,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6: hat problemlos geklappt,\nNA. Item was never rendered for this user.",
      "maxValue": 6,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "cbk",
      "description": "Hatten Sie schon die Gelegenheit das codebook package auszuprobieren?",
      "value": "1. nein,\n2. kurz reingeschaut,\n3. ja,\nNA. Item was never rendered for this user.",
      "maxValue": 3,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "rmd_01",
      "description": "Wie oft haben Sie schon mit R Markdown gearbeitet?",
      "value": "1. 1: noch nie,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6: sehr oft,\nNA. Item was never rendered for this user.",
      "maxValue": 6,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "rmd_02",
      "description": "Ich weiß, wie ich in R Markdown Textformatierungen vornehmen kann.",
      "value": "1. 1: gar nicht,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6: vollständig,\nNA. Item was never rendered for this user.",
      "maxValue": 6,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "rmd_03",
      "description": "Ich weiß, wie ich in R Markdown ein HTML Dokument erstelle, in dem der Analysecode und die Ergebnisse meiner statistischen Auswertungen enthalten sind.",
      "value": "1. 1: hell no,\n2. 2,\n3. 3,\n4. 4,\n5. 5,\n6. 6: hell yes,\nNA. Item was never rendered for this user.",
      "maxValue": 6,
      "minValue": 1,
      "measurementTechnique": "self-report",
      "@type": "propertyValue"
    },
    {
      "name": "sof",
      "description": "aggregate of 3 sof items",
      "@type": "propertyValue"
    },
    {
      "name": "rmd",
      "description": "aggregate of 3 rmd items",
      "@type": "propertyValue"
    }
  ]
}`